class_docstr: Tests for SkLearnMutualInformationStatsFn.
docstr: Checks that MI computation is correct.
docstr_tok: ["Checks","that","MI","computation","is","correct","."]
code: def _assert_mi_output_equal(
      self, batch, expected, schema, label_feature
  ):
      """Checks that MI computation is correct."""
      actual = sklearn_mutual_information.SkLearnMutualInformation(
          label_feature, schema, TEST_SEED
      ).compute(batch)
      compare.assertProtoEqual(
          self, actual, expected, normalize_numbers=True
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import absltest
  import numpy
  import pyarrow
  from tensorflow_data_validation import types
  from tensorflow_data_validation.statistics.generators import sklearn_mutual_information
  from google.protobuf import text_format
  from tensorflow.python.util.protobuf import compare
  from tensorflow_metadata.proto.v0 import schema_pb2
  from tensorflow_metadata.proto.v0 import statistics_pb2
label_desc: Use image node_id 1 for calling the SkLearnMutualInformationTest obj's underlying member method code with example usage: obj._assert_mi_output_equal(batch, expected, schema, label_feature) without return types